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What is...

cortx_dicom?

Cortx_dicom is a dicom integration into Seagate's CORTX server in Python. Handling dicom files is based on pydicom. It has 5 major functionalities:

  • collecting metadata [ cortx_dicom and pydicom ]
  • managing data [ S3 ]
  • searching [ Elasticsearch ]
  • warning about potential legal and data risks [ cortx_dicom ]
  • removing protected health information from dicom [ pydicom ]

We already integrated 4840 dicom tags into our system as the base of the labeling method. For the legal parts, we implemented the warning features for 256 potentially risky tags.

CORTX?

CORTX is 100% open source object storage system with features like mass capacity and great efficiency.

dicom?

Dicom is a widely used standard in healthcare to store and transmit medical imaging information and related data.

How it works?

Cortx_dicom can be used locally with a CORTX-VirtualMachine (VM) or remotely with a cloud-based server.

Video presentation

This video is about cortx_dicom presentation and it is part of the submission.

Project presentation video (submission video): https://youtu.be/Qxb3cFnwXnQ

This video is a code walkthrough and it is NOT the part of the submission.

Code walkthrough video (outside submission): https://youtu.be/emRk4xqBDmQ

How to use?

  • At the moment you cannot install cortx_dicom as a python module however it was developed in a way to do so in the future. It has a requirements.txt file to install requirements easily.

  • First of all, you need to have a working CORTX server. It can be a VM or a cloud instance.

  • Since cortx_dicom uses pydicom, you should install it with the following command pip install pydicom or if you are an Anaconda user, feel free to use the conda install -c conda-forge pydicom command. This step is skippable if you have installed all of the dependencies via our requirements.txt.

  • Cortx_dicom uses elasticsearch for searching, so you should install it with the following command pip install elasticsearch. This step is skippable if you have installed all of the dependencies via our requirements.txt.

  • Cortx_dicom uses boto3 for handling S3 buckets, so you should install it with the following command pip install boto3. This step is skippable if you have installed all of the dependencies via our requirements.txt.

  • There is a config.json file with the most important configuration keys. If you have a local VM or any other access to cortx you just have to update the data there.

Examples

In this section we show how the main functions work. Examples are not in alphabetical order, but in the order as it can happen during a real-life usage. For testing purposes, we provide some test dicom files. For more details, please check the example.py or the docstrings of the code. The source of dicom files is: https://github.com/datalad/example-dicom-structural.

Search for dicom file

CortxDicom.search(search_expression, index, just_find)

  • search_expression: Parameter to be searched. If string is given, it is treated as an Id to get. If a tuple is given it is treated as a simple key = value search. If dict is given it is directly forwarded to elasticsearch as a query.

  • index: Name of the index to get.

  • just_find: Whether to return a bool with the result of the search or return information about the found object(s).

Real example for matching all. It is useful when you want to test the code or any function, since it always returns with something.

result = cortxdicom.search({"query": {"match_all": {}}}, just_find=False)

Get a dicom file

CortxDicom.get(search_expression, object_key, bucket, index)

  • search_expression: Parameter to be searched. If string is given, it is treated as an Id to get. If a tuple is given it is treated as a simple key = value search. If dict is given it is directly forwarded to elasticsearch as a query. If None is given S3 is used.

  • index: Name of the index to get.

  • object_key: The name (key) to get the object in s3 with.

  • bucket: Name of the bucket to store.

Real example for getting dicom file with S3

result = cortxdicom.get(object_key=s3_ids[0], bucket=TEST_BUCKET)

Describe dicom files

CortxDicom.describe(dicom_object, key_scheme)

  • dicom_object: Path of a DICOM file, or the DICOM file's instance.

  • key_scheme: Scheme of DICOM keys to add. Available schemes: KEY_SCHEME_HUMAN_READABLE, KEY_SCHEME_NUMERIC, KEY_SCHEME_SPACELESS

Real example for printing the content of a dicom file in a human readable format.

print(CortxDicom.describe(dicomfile, CortxDicom.KEY_SCHEME_HUMAN_READABLE))

Using filters

CortxDicom.apply_filter(dicom_object, filter_type)

  • dicom_object: Path of a DICOM file, or the DICOM file's instance.

  • filter_type: Filters to apply. Available filters: FILTER_NO_FILTER, FILTER_PRIVATE, FILTER_HIPAA, FILTER_GDPR

Real example for applyling HIPAA filter on a dicom file. WARNING: Deleting from a pydicom instance usually mean inplace operation. This means it is not necessarily to use the returned variable.

CortxDicom.apply_filter(dicomfile, CortxDicom.FILTER_HIPAA)

Store a dicom file

CortxDicom.store(dicom_object, object_key, bucket, index, allow_overwrite)

  • dicom_object: Path of a DICOM file, or the DICOM file's instance.

  • object_key: The name (key) to store the object in s3 with. If empty string is given, a new random name is generated.

  • bucket: Name of the bucket to store. If empty string is given, bucket name is retrieved from the configuration.

  • index: Name of the index to store.

  • allow_overwrite: Whether or not to allow to overwrite existing object.

Real example for storing a dicom file in a test bucket.

es_id = cortxdicom.store(dicomfile, bucket=TEST_BUCKET)

Why should you used cortx_dicom?

CORTX is an open source solution. Cortx_dicom can help you to handle dicom files on a legally proper way to meet the requirements of different regulations like HIPAA, GDPR or CCPA.